{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "from datetime import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams['font.sans-serif'] = ['fangsong']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams['axes.unicode_minus'] = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "sales = [5, 22, 48, 78]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "dates = ['19-03-01', '19-03-12', '19-03-16', '19-03-31']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "days = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "for d in dates:\n",
    "    delta = datetime.strptime(d, '%y-%m-%d') - datetime.strptime(dates[0], '%y-%m-%d')\n",
    "    days.append(delta.days)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1b0dbcb1280>]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.grid()\n",
    "plt.title('销量')\n",
    "plt.xticks(days, dates)  # plt.xticks(真实刻度，标签)\n",
    "plt.plot(days, sales)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1b0b8a837c0>]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(dates, sales)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1b0dba41790>]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.grid()\n",
    "plt.title('销量')\n",
    "plt.plot(days, sales)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
